Interpretable models are ML techniques that learn more structured, interpretable, or causal models
. Early examples included Bayesian rule lists (Letham et al.
I followed a two-step process entailing confirmatory factor analysis (CFA) and structural equation analysis for the causal model
. Before the analysis, an assumption test was applied to see if the data satisfied multivariate normality.
Overall, decision-tree and Bayesian causal models
show some similarities and differences in prediction results.
A parameterized causal model
allows it to make specific predictions of the probabilities of individual events or patterns of events within the causal model
As explained in the covering law and causal models
, the premise is a 'law-like' generalisation or known fact that is accepted in the community.
Constructing and testing the predictive model of alcohol consumption relapse on the basis of socio-demographic variables; retaining the optimum model; (3) Constructing and testing the causal model
for dependent variables (alcohol consumption and relapses); (4) Comparative analysis of the women group vs.
Keywords: causal model
, quality of education, educational management, graduate education
It is started with the causal model
as it allows to state that health problems must include the dialectical relationship between chance and necessity, between casual and causal versus the determinism and the mechanism prevailing in the analysis of health science.
In addition to assessing the group of students as a whole, an additional set of analyses were employed to compare students who were more and less successful in teaching Betty the correct causal model
. The goal was to investigate whether or not success in the system was associated with higher levels of effectiveness and action support.
In natural concepts, features often represent causes or effects with the category label referring to a complex causal model
. For example, disease categories frequently refer to common-cause models of diseases with the category features representing causes (e.g., virus) and effects (e.g., symptoms) within this causal model
This study proposes a causal model
based on the DEMATEL methodologies to support green supply chain management strategic decisions and green supplier selection.
Path analysis was used to test the causal model
to the extent the observed variables were representative of the latent constructs of the hypothesized model.